Work

Network pharmacology and in silico investigation into the therapeutic potential of phytoconstituents of Peucedanum ostruthium as anti-tubercular agents

Year: 2025

Type: article

Abstract: • Peucedanum ostruthium often referred as masterwort. • Swiss target prediction was used to determine the target genes. • The DisGeNET datasets were used to extract genes and variations associated with TB. • The examination of gene-gene interactions was conducted using the STRING database. • Kampeferol-3-O-rutinoside exhibits stronger binding affinities to MmpL3. Mycobacterium tuberculosis is the causative agent of tuberculosis (TB) globally. Despite significant progress in biomedical research, novel treatment strategies, and preventative measures, the incidence rates of TB continue to rise. Peucedanum ostruthium , often called masterwort , is a flowering plant from the Apiaceae family used to treat various ailments. However, the specific biochemical mechanism behind its therapeutic effect remains unidentified. The phytoconstituents of P. ostruthium were studied using Swiss Target Prediction to determine the target genes. The DisGeNET datasets were used to extract genes and variations associated with TB. Gene-gene interactions were examined using the STRING database, while gene enrichment analysis was done using the SR Plot database. P. ostruthium identified nine active constituents that have 256 potential therapeutic targets. In addition, the docking studies demonstrated that kampeferol-3-O-rutinoside exhibits stronger binding affinities to the Mycobacterial membrane protein Large 3 (MmpL3). This study presents compelling evidence that P. ostruthium may be effectively used to target TB after experimental validation. Additionally, it establishes a novel basis for additional experimental investigations into the anti-tubercular properties of P. ostruthium .

Source: Health Sciences Review

DOI: 10.1016/j.hsr.2025.100219

Authors: Neeru Bhanwala, Raunak Katiyar, Sumit Kumar, Ashok K. Datusalia, Gopal L. Khatik

Institutions: National Institute of Pharmaceutical Education and Research, National Institute of Pharmaceutical Education and Research

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,020